Financial Evidence for AI agents
Read-only MCP and API research infrastructure for AI finance and trading agents. Connect to funding, bank-risk, market-liquidity and economic evidence while keeping source dates, coverage gaps and rights attached to the result. Operated by LIQUILENS PRIVATE LIMITED.
Install
Python 3.10 or newer:
python3 -m pip install 'financial-evidence[workspace]==0.1.9'
financial-evidence-trading doctor
financial-evidence-trading context
The workspace extra supplies the MCP/HTTP dependencies needed by the persistent
clients. The base package has no required dependencies and includes the terminal
and three-tool stdio router. Public hosted research reads need no data API key.
Optional subscriptions and client/model costs have separate terms.
Reuse an MCP connection
import asyncio
from financial_evidence.trading import ProductClient
async def main():
async with ProductClient(mode="test", timeout=15) as client:
first = await client.call("seiche", "data_health")
again = await client.call("seiche", "data_health")
print(first["timing"], again["timing"])
asyncio.run(main())
mode="test" labels verification traffic. Repeated reads reuse the bounded
session; failed requests are not automatically replayed. Session reuse does not
make source data fresher or grant trading authority.
Read compact source-status updates
import asyncio
from financial_evidence.trading.context import ContextClient
async def main():
async with ContextClient() as client:
snapshot = await client.snapshot()
print(snapshot)
asyncio.run(main())
The public source-status routes are:
These report metadata, not live quotes. Source freshness, source rights and stream liveness are separate. See the Python/JavaScript stream guide for expiry, reset and reconnect handling. The JavaScript companion is available from that guide and is not represented as a Python module.
Connect an MCP client
For hosted financial research, add this Streamable HTTP endpoint:
https://agents.seiche.info/products/financial-evidence/mcp
Start with financial_evidence_agent_query and
{"dataset":"money_markets","entity":"USD","limit":3}.
Download the product MCP configurations
for LiquiLens, Seiche, Undertow, Palimpsest and the other explicitly labelled
research, metadata and sandbox surfaces. Each endpoint has its own tool schema.
For the local three-tool research router:
uvx --from financial-evidence==0.1.9 financial-evidence mcp
The existing financial-evidence-mcp command remains available. The local router
exposes financial_evidence_topics, financial_evidence_route and
financial_evidence_fetch; it is separate from the hosted Research Desk tool set.
Diagnostics and source admission
financial-evidence-trading latency --samples 3 performs labelled synthetic reads.
source-access inspects the permission catalog, while feed-pilot runs invented
recovery fixtures. Neither obtains a feed licence, executes a trade or establishes
a production latency guarantee. Preserve unavailable and restricted results.
Setup guide · Source · Issues · Licence
Metadata
Release files for financial-evidence 0.1.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| financial_evidence-0.1.9.tar.gz | 3.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| financial_evidence-0.1.9-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.7 MB
Release files / financial_evidence-0.1.9.tar.gz
| Download URL | financial_evidence-0.1.9.tar.gz |
|---|---|
| Size | 3.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / financial_evidence-0.1.9-py3-none-any.whl
| Download URL | financial_evidence-0.1.9-py3-none-any.whl |
|---|---|
| Size | 176.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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0e13875e0ce0c8b4e202a620ebbe24ff74b21ece2b67bf002801b95a24cd1ba4
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 15, 2026.
Transparency log